National Research Platform (NRP)

Quick Links: | Article Summary | Getting Access to NRP and Nautilus | Using NRP Nautilus Resources | Training Resources | Support and Questions |

Article Summary  

The National Research Platform (NRP) is a community-owned research and education platform that provides access to advanced computing, storage, and networking technologies. Supported by many institutions and funded in part by the National Science Foundation, NRP helps accelerate research and education in fields such as data science, machine learning, and artificial intelligence. At its core is Nautilus, a large distributed cluster that integrates high-performance GPUs, fast data transfer, and scalable storage across dozens of sites.

Chico State faculty members and researchers can use NRP and Nautilus for research projects, coursework, and training. Resources are accessible through command-line tools or easy-to-use interfaces like JupyterLab, making it possible to scale from individual experiments to large, collaborative projects.

Getting Access to NRP and Nautilus  

  1. Go to the NRP Nautilus portal.
  2. Click Log In at the top right corner.
  3. You will be redirected to the CILogon page:
    • Select your institution (Chico State) if listed.
    • If not listed, try Microsoft (Office 365/Active Directory), Google, or GitHub as alternatives.
    • Log in with your Chico State institutional credentials.
  4. On your first login, your account will be created with guest status. Guests cannot yet run code.
  5. Students: Contact your faculty research supervisor to be added to their namespace (a project group). Once added, your account will be promoted to user and you will gain cluster access.
  6. Faculty members and researchers: You may request to create your own namespace (for a research group or class project) and become a namespace admin. This request is made via the Matrix support channel.

Using NRP Nautilus Resources  

Once you have user access, you can take advantage of the platform’s computing and data tools:

  • JupyterLab: A web-based notebook environment for coding, data analysis, and machine learning. Easy to use—no local installation required.
  • Kubernetes via kubectl: Advanced users can interact with Nautilus through the Kubernetes command line to launch pods, manage jobs, and scale workloads.
  • Data Storage: Large datasets can be mounted and used across the cluster, ensuring fast access wherever your jobs run.
  • GPU Access: Access to standard GPUs (NVIDIA RTX series) and high-memory GPUs (e.g., NVIDIA A100 Tensor Core) for deep learning and AI training tasks.

New users are strongly encouraged to complete the NRP Nautilus tutorials for step-by-step guidance on launching jobs, requesting storage, and using containers.

Training Resources  

Training on how to use NRP and Nautilus is available through recorded sessions and live Zoom links. Visit the official NRP Training page to access upcoming training events, recordings, and materials to help you get started.

Support and Questions  

Please note that Chico State’s Division of IT (DoIT) is unable to provide support for faculty members or researchers using the NRP. For assistance, use the official NRP support resources:

Before You Ask for Support

To help the NRP support team respond effectively, gather the following before posting your question:

  • Namespace and Pod Name: If your issue relates to a pod, include the namespace and pod name.
  • Minimal Reproducible Example (MRE): Provide a short code snippet or example that demonstrates the problem, if possible.
  • Pod Status and Logs: Run kubectl describe pod <pod-name> -n <namespace> and kubectl logs <pod-name> -n <namespace> to capture relevant output.
  • Error Messages: Include any error text you see in your job or notebook.
  • Clear Description: Be concise and specific about what you expected to happen and what occurred instead.

Following this checklist will improve the chances of receiving a faster and more accurate response from the NRP community and support team.

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